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The artificial viscosity approach for curing the carbuncle phenomenon (a numerical problem, also known as the shock instability) in shock-capturing methods has been recently presented and successfully tested on the first-order schemes in…

Numerical Analysis · Mathematics 2018-12-27 Alexander V. Rodionov

We propose and analyse a hybrid high-order (HHO) scheme for stationary incompressible magnetohydrodynamics equations. The scheme has an arbitrary order of accuracy and is applicable on generic polyhedral meshes. For sources that are small…

Numerical Analysis · Mathematics 2023-02-21 Jérôme Droniou , Liam Yemm

The dynamics of supercooled liquid and glassy systems are usually studied within the Lagrangian representation, in which the positions and velocities of distinguishable interacting particles are followed. Within this representation,…

Disordered Systems and Neural Networks · Physics 2009-09-28 Claudio Chamon , Leticia F. Cugliandolo , Gabriel Fabricius , Jose Luis Iguain , Eric R. Weeks

In this paper, we propose a method for constructing a neural network viscosity in order to reduce the non-physical oscillations generated by high-order Discontiuous Galerkin (DG) methods. To this end, the problem is reformulated as an…

Numerical Analysis · Mathematics 2023-09-22 L éo Bois , Emmanuel Franck , Laurent Navoret , Vincent Vigon

The smoothed particle hydrodynamics (SPH) method has been widely used to simulate incompressible and slightly compressible fluid flows. Adaptive refinement strategies to dynamically increase the resolution of the particles to capture sharp…

Fluid Dynamics · Physics 2024-07-31 Abhinav Muta , Pawan Negi , Prabhu Ramachandran

Recently, lower-level constrained bilevel optimization has attracted increasing attention. However, existing methods mostly focus on either deterministic cases or problems with linear constraints. The main challenge in stochastic cases with…

Optimization and Control · Mathematics 2025-10-13 Hantao Nie , Jiaxiang Li , Zaiwen Wen

The Smoothed Particle Hydrodynamics (SPH) is a particle-based, Lagrangian method for fluid-flow simulations. In this work, fundamental concepts of this method are first briefly recalled. Then, the ability to accurately model granular…

Geophysics · Physics 2016-02-26 Kamil Szewc

This paper presents a new approach and algorithm for solving a class of constrained Bi-Level Optimization (BLO) problems in which the lower-level problem involves constraints coupling both upper-level and lower-level variables. Such…

Machine Learning · Computer Science 2024-01-30 Wei Yao , Chengming Yu , Shangzhi Zeng , Jin Zhang

Model-based controllers can offer strong guarantees on stability and convergence by relying on physically accurate dynamic models. However, these are rarely available for high-dimensional mechanical systems such as deformable objects or…

Robotics · Computer Science 2026-02-10 Katharina Friedl , Noémie Jaquier , Seungyeon Kim , Jens Lundell , Danica Kragic

In the present work, we consider multi-scale computation and convergence for nonlinear time-dependent thermo-mechanical equations of inhomogeneous shells possessing temperature-dependent material properties and orthogonal periodic…

Numerical Analysis · Mathematics 2023-08-23 Hao Dong , Xiaofei Guan , Yufeng Nie

In this chapter, we aim at presenting the basic techniques necessary to go beyond the widely accepted paradigm of second-order numerics. We specifically focus on finite-volume schemes for hyperbolic conservation laws occuring in fluid…

Numerical Analysis · Mathematics 2024-07-29 Jean-Mathieu Teissier , Wolf-Christian Müller

We propose a novel high-order HDG method for the Biot's consolidation model in poroelasticity. We present optimal error analysis for both the semi-discrete and full-discrete (combined with temporal backward differentiation formula) schemes.…

Numerical Analysis · Mathematics 2018-04-30 Guosheng Fu

We study optimization algorithms based on variance reduction for stochastic gradient descent (SGD). Remarkable recent progress has been made in this direction through development of algorithms like SAG, SVRG, SAGA. These algorithms have…

Machine Learning · Computer Science 2016-01-26 Sashank J. Reddi , Ahmed Hefny , Suvrit Sra , Barnabás Póczos , Alex Smola

We present a new accelerated stochastic second-order method that is robust to both gradient and Hessian inexactness, which occurs typically in machine learning. We establish theoretical lower bounds and prove that our algorithm achieves…

Optimization and Control · Mathematics 2024-05-28 Artem Agafonov , Dmitry Kamzolov , Alexander Gasnikov , Ali Kavis , Kimon Antonakopoulos , Volkan Cevher , Martin Takáč

In this paper, we study stochastic non-convex optimization with non-convex random functions. Recent studies on non-convex optimization revolve around establishing second-order convergence, i.e., converging to a nearly second-order optimal…

Optimization and Control · Mathematics 2017-11-02 Mingrui Liu , Tianbao Yang

A cell-centered implicit-explicit updated Lagrangian finite volume scheme on unstructured grids is proposed for a unified first order hyperbolic formulation of continuum fluid and solid mechanics. The scheme provably respects the stiff…

Numerical Analysis · Mathematics 2022-01-26 Walter Boscheri , Simone Chiocchetti , Ilya Peshkov

We analyse the performance of twelve different implementations of Smoothed Particle Hydrodynamics (SPH) using seven tests designed to isolate key hydrodynamic elements of cosmological simulations which are known to cause the SPH algorithm…

Astrophysics · Physics 2009-10-30 R. J. Thacker , E. R. Tittley , F. R. Pearce , H. M. P. Couchman , P. A. Thomas

In this paper we genealize the fast semi-Lagrangian scheme developed in [J. Comput. Phys., Vol. 255, 2013, pp 680-698] to the case of high order reconstructions of the distribution function. The original first order accurate semi-Lagrangian…

Numerical Analysis · Mathematics 2016-03-16 Giacomo Dimarco , Cory Hauck , Raphaël Loubère

We propose a Hybrid High-Order (HHO) formulation of the incompressible Navier-Stokes equations with variable density that provides exact conservation of volume and, accordingly, pure advection of the density variable. The spatial…

Fluid Dynamics · Physics 2026-05-14 Lorenzo Botti , Francesco Carlo Massa

Robot programming tools ranging from inverse kinematics (IK) to model predictive control (MPC) are most often described as constrained optimization problems. Even though there are currently many commercially-available second-order solvers,…

Robotics · Computer Science 2023-07-03 Hakan Girgin , Tobias Löw , Teng Xue , Sylvain Calinon